Literature DB >> 35089966

Associations between pain and physical activity among older adults.

Nils Georg Niederstrasser1, Nina Attridge1.   

Abstract

OBJECTIVES: Chronic pain is a significant societal problem and pain complaints are one of the main causes of work absenteeism and emergency room visits. Physical activity has been associated with reduced risk of suffering from musculoskeletal pain complaints, but the exact relationship in an older adult sample is not known.
METHODS: Participants self-reported their physical activity level and whether they were often troubled by bone, joint, or muscle pain. Logistic regression analyses revealed the nature of the relationship between musculoskeletal pain and physical activity cross-sectionally and longitudinally over the course of 10 years. Data were taken from the English Longitudinal Study of Ageing, comprising of 5802 individuals residing in England aged 50 or older.
RESULTS: Only high levels of physical activity were associated with a reduced risk of suffering from musculoskeletal pain compared to a sedentary lifestyle longitudinally. In addition, having low wealth, being female, and being overweight or obese were found to be risk factors for suffering from musculoskeletal pain.
CONCLUSIONS: The development of interventions aimed at alleviating and preventing musculoskeletal pain complaints might benefit from incorporating physical activity programs, weight loss, and aspects addressing wealth inequality to maximise their efficacy.

Entities:  

Mesh:

Year:  2022        PMID: 35089966      PMCID: PMC8797193          DOI: 10.1371/journal.pone.0263356

Source DB:  PubMed          Journal:  PLoS One        ISSN: 1932-6203            Impact factor:   3.240


Introduction

Chronic pain is related to considerable societal costs that stem from greater use of health care and reduced work productivity [1]. It presents one of the most widespread and complex problems in the medical community [2], as sufferers report decreased quality of life, and poor physical, social, and psychological well-being alongside their pain complaints [3, 4]. The prevalence of pain increases with age, with up to 62% of the over 75 age group in the UK reporting persistent pain complaints [5]. Perplexingly, however, there is an under-representation of older adults in pain clinics and pain management programmes [6]. Negative attitudes toward pain treatment, especially in terms of perceived lack of efficacy and concerns over adverse side effects as well as addiction, the belief in the inevitability of pain in old age, and pain complaints’ perceived low importance compared to other comorbidities may explain why older adults are reluctant to seek treatment for pain [7]. In an ageing society, pain will pose an ever-increasing challenge. It is therefore imperative to identify what predisposes individuals to develop persistent pain complaints, so that interventions may be developed to prevent and reduce chronic pain. Studies have suggested that sedentary behaviour may lead to disuse symptoms and result in greater pain sensitivity [8], while being physically active may have protective effects against the occurrence of pain and its consequences [9]. It is not clear, however, how these findings relate to older adults [10-12]. Older adults have a higher incidence of chronic pain [13] and are generally less physically active than younger adults [14]. Only 1 in 4 adults over 65 engage in the minimum recommended activity levels needed to maintain health [15], suggesting that sedentariness may be a major contributor to pain complaints among older adults. Most examinations into the relationship between physical activity and pain have been cross-sectional [16, 17], with few longitudinal exceptions [18]. None, to date, have examined this relationship specifically in a large sample of older adults. The lack of longitudinal studies among older adults specifically is alarming, as potential risk factors, such as sedentariness, are more common but take time to lead to pain. This relationship may be obscured by cross-sectional investigations, as sedentary behaviour may be both a risk and a result of pain complaints. The impact of pain is often more severe among older adults [13] and it frequently occurs alongside multiple comorbidities further limiting treatment options and highlighting the need for preventative action [19]. Furthermore, up to 60% of care home residents suffer from some form of cognitive impairment that limits the ability to communicate pain, leading to both over and under-treatment of pain [20]. There is also a great level of variability in the assessment of both physical activity and pain, which may obscure more nuanced relationships [21] and so the exact nature of the long-term association between physical activity and pain among older adults remains elusive. Furthermore, there may be additional factors associated with greater propensity to report pain complaints in older age. Several such factors have been suggested for the general population, including female gender [22, 23], being overweight [24], and wealth levels [25]. Persistent pain is more common among women than men [22, 23], which may be related to an increased sensitivity to pain that leads to more frequent widespread pain and higher reported pain intensity. Being overweight may cause excess mechanical stress predisposing individuals to develop persistent pain [24] and higher levels of proinflammatory cytokines that may produce a hyperalgesic state [26]. Economic stress and associated depressive symptomology stemming from low wealth levels may also predispose individuals towards developing pain complaints [25]. While there is evidence suggesting these factors may confound the relationship between physical activity and pain, their cumulative effects in a sample of older adults remain elusive. Here, data from the English Longitudinal Study of Ageing (ELSA) are used to examine whether physical activity, adjusting for gender, age, wealth level, and being overweight or obese, predicts the risk of reporting persistent musculoskeletal pain either cross-sectionally or longitudinally over the course of ten years.

Methods

Sample

ELSA is an ongoing longitudinal study that gathers data from a representative sample of adults aged 50 years and over living in England. Details pertaining to data collection methods and sampling details are available elsewhere [27]. Currently, data from nine waves are available, collected between 2002/2003 and 2020/2021, with two-year intervals between waves. The current study draws on data from waves 2 (2004/2005), 4, (2008/2009), 7 (2014/2015), and 9 (2018/2019). With each wave, new participants are added to maintain a steady sample. Waves 1 and 3 do not include information on relevant risk factors and so had to be excluded. Since the longitudinal assessment spans 10 years, participants present in either waves 2 and 7 or 4 and 9 were eligible for inclusion in the current study. In other words, some participants’ data were collected between 2004/2005 and 2014/2015 and others’ were collected between 2008/2009 and 2018/2019. Baseline data were taken from waves 2 (2004/2005) and 4 (2008/2009). Data were collected through a combination of nurse assessments and self-report measures. Participants gave fully informed written consent to participate in the study. The London Multicentre Research Ethics Committee (MREC/01/2/91) granted ethical approval for the data collection and archiving.

Outcome—Ffrequent musculoskeletal pain

Participants self-reported whether they were often troubled by bone, joint, or muscle pain (yes/no) at waves 2, 4, 7, and 9. This variable has been used in previous investigations using the ELSA dataset [28].

Physical activity level

Participants indicated the frequency of taking part in mild, moderate, and vigorous activities during leisure time, selecting from the following options for each level of intensity: (1) more than once per week, (2) once per week, (3) one to three times per month, or (4) hardly ever. Participants were shown prompt cards depicting examples of activities and corresponding intensity levels to aid them in finding the appropriate intensity level of their leisure activity. Examples of vigorous activity included: swimming, digging with a spade, jogging or running, cycling, and tennis; moderate: dancing, floor/stretching exercises, walking at a moderate pace, gardening and washing the car; mild: doing laundry, vacuuming, and home repairs. The questions pertaining to physical activity status were taken from a validated physical activity interview [29]. Participants were categorised into four mutually exclusive groups (sedentary, mild, moderate, and vigorous), based on the highest intensity of physical activity that was carried out at least once per week [30]. For example, someone who did mild physical activity up to three times per month would be assigned to the “sedentary” group, while someone who did laundry every week and cycling once per month would be assigned to the “mild” group. Participants were also asked to indicate the physical activity level of the work they do most of the time, with the options of sedentary occupation (most time spent sitting), standing occupation (most time spent standing or walking, but not requiring intense physical effort), physical work (requiring some physical effort such as handling of heavy objects and use of tools), and heavy manual work (requiring very vigorous physical activity including handling of very heavy objects). Participants were assigned to categories of physical activity based on the following criteria: Sedentary: Not working or sedentary occupation, engages in mild exercise 1–3 times a month or less, with no moderate or vigorous activity. Low: Standing occupation, engages in moderate leisure-time exercise once a week or less and no vigorous activity; or engages in mild leisure-time activity at least 1–3 times a month, moderate once a week or less and no vigorous; or has a sedentary or no occupation and engages in moderate leisure-time activity once a week or 1–3 times a month, with no vigorous activity. Moderate: Does physical work; or engages in moderate leisure-time activity more than once a week; or engages in vigorous activity once a week to 1–3 times a month. High: Heavy manual work or vigorous leisure activity more than once a week.

Covariates in the association between physical activity and persistent musculoskeletal pain

These additional predictor variables were assessed either during nurse visits or self-reported during data collection for waves 2 and 4.

Body Mass Index (BMI)

During nurse visits participants’ standing height (meters) and body mass (kilograms) were measured. Participants exceeding a body mass of 130 kg were excluded from the measurement, as the scales had a maximum weight capacity of 130 kg. In these cases, body mass was estimated. Body mass index was quantified as dividing body mass (kg) by standing height (meters) squared (kg/m2). The following categories were used: BMI < 18.5 underweight; BMI between 18.5 and 25 normal weight; BMI between 25 and 30 overweight; BMI > 30 obese.

Age

Ages over 90 were collapsed into a single age group, to protect participants’ identities.

Sex

Sex was self-reported by participants during interviews.

Wealth quintile

Wealth was determined by dividing participants into quintiles based on their net wealth. Net wealth was quantified as the net sums of housing wealth, physical wealth (including additional property wealth, wealth related to business and other physical assets) and financial wealth (including savings, stock certificates and bank accounts) after financial debt and mortgage debt had been subtracted.

Statistical approach

All analyses were performed using R version 4.1. The outcome variable “Musculoskeletal Pain” was quantified as binary (are you often troubled by pain: “yes”/ “no”) and three logistic regression analyses, using the R-package “glm”, were used to assess the relationship between physical activity and musculoskeletal pain a) cross-sectionally and b) longitudinally.

Cross-sectional analysis

We ran a logistic regression analysis with musculoskeletal pain at baseline as the dependent variable and age, physical activity level, BMI, gender, and wealth quintile as predictor variables.

Longitudinal analyses

We ran two logistic regression analyses with musculoskeletal pain at follow up (10 years after baseline) as the dependent variable and age, physical activity level, BMI, gender, wealth quintile, and musculoskeletal pain at baseline as predictor variables. The first analysis comprised of the entire data. The second analysis included only those reporting to be pain free at baseline and therefore musculoskeletal pain at baseline was not used as a predictor variable in this analysis. Odds ratios for the continuous and each level of the categorical predictors in each analysis were calculated. In cases where data for participants were available for the ten years following wave 2 and 4, data from wave 2 were used as baseline. Wherever data were available only from wave 4, these were used as baseline. Outcome data were taken from waves 7 and 9 based on which wave was used as baseline.

Results

Sample characteristics

In total, data from 5802 individuals (mean age 62.3, SD = 7.7; 2559 (44.1%) males), were available over a period of ten years. Table 1 presents the means and standard deviations as well as counts for the categorical variables.
Table 1

Sample overview.

Variables
Troubled by musculoskeletal pain Yes No
 Baseline2062 (35.5%)3740 (64.5%)
 10-year follow-up Yes No
2461 (42.4%)3341 (57.6%)
Sex Male Female
2559 (44.1%)3243 (55.9%)
Age—mean (SD)62.3 (7.7)
Physical activity level (n)
Sedentary 122 (2.1%)
Mild1124 (19.4%)
Moderate3137 (54.1%)
High1419 (25.5%)
BMI categories (n)
Underweight34 (0.6%)
Normal 1547 (26.7%)
Overweight2496 (43.0%)
Obese1725 (29.7%)
Wealth Quintiles
Low 751 (12.9%)
Low to Medium1005 (17.3%)
Medium1158 (20.0%)
Medium to High1330 (22.9%)
High1558 (26.9%)

N = 5802; unless otherwise indicated, variables refer to those taken at baseline;

for categorical variables reference categories are printed in bold;

N = 5802; unless otherwise indicated, variables refer to those taken at baseline; for categorical variables reference categories are printed in bold;

Cross-sectional relationship between physical activity and pain

At baseline, 2062 participants reported being troubled by musculoskeletal pain. Participants’ age, physical activity level, BMI, gender, and wealth quintile were entered into the regression equation in one step. Values from the final regression equation (see Table 2) indicated that mild, moderate, and high physical activity were associated with a lower likelihood of suffering from musculoskeletal pain compared to being sedentary. Similarly, belonging to a higher wealth quintile was associated with being less likely to suffer from musculoskeletal pain. Being female, overweight or obese were risk factors associated with an increased likelihood of suffering from musculoskeletal pain complaints.
Table 2

Logistic regression for the cross-sectional relationship between physical activity and musculoskeletal pain.

β (SE)Odds Ratio (95% Confidence Interval)
Intercept1.27 (0.30)
Age0.01 (0.00)1.01 (1.00–1.01)
Reference category: sedentary PA
 mild PA-0.72 (0.21)**0.49 (0.32–0.74)
 moderate PA-1.39 (0.21)**0.25 (0.16–0.37)
 high PA-1.58 (0.22)**0.21 (0.13–0.31)
Reference category: normal weight
 underweight0.04 (0.39)1.04 (0.47–2.16)
 overweight0.23 (0.07)**1.26 (1.09–1.46)
 obese0.65 (0.08)**1.91 (1.64–2.23)
Reference category: male gender
 female gender0.28 (0.06)**1.33 (1.18–1.49)
Reference category: Low Income
Low to Middle-0.40 (0.10)**0.67 (0.55–0.82)
Middle-0.58 (0.09)**0.56 (0.46–0.68)
Middle to High-0.67 (0.10)**0.51 (0.42–0.62)
High-0.74 (0.10)**0.48 (0.39–0.57)

N = 5802;

* p < .05;

** p < .01;

Beta weights are from the final regression equation;

R2 for final regression equation = .11 (Nagelkerke), Model x2(12) = 461.68, p < .01;

N = 5802; * p < .05; ** p < .01; Beta weights are from the final regression equation; R2 for final regression equation = .11 (Nagelkerke), Model x2(12) = 461.68, p < .01;

Longitudinal relationship between physical activity and pain

Next, we examined the association between physical activity and musculoskeletal pain in the 10 years following baseline. The first analysis included all 5802 participants. Participants’ age, physical activity level, BMI, gender, wealth quintile, and pain status at baseline were entered into a logistic regression equation in one step, with pain status at follow up as the dependent variable. Out of 5802 participants, 2461 participants reported being frequently troubled by musculoskeletal pain ten years after baseline. Beta weights for the final regression equation (see Table 3) indicated that engaging in high physical activity was associated with lower probability of reporting being troubled by musculoskeletal pain ten years later. Participants in the highest three wealth quintiles were also less likely to report suffering from musculoskeletal pain compared to those in the lowest quintile. Being female, overweight, or obese was associated with an increased the risk of suffering from musculoskeletal pain complaints after ten years.
Table 3

Logistic regression for the longitudinal relationship between physical activity and musculoskeletal pain.

β (SE)Odds Ratio (95% Confidence Interval)
Intercept1.27 (0.30)
Reference category: No current musculoskeletal pain
Existing musculoskeletal pain1.53 (0.06)**4.60 (4.01–5.20)
Age-0.00 (0.00)1.00 (1.00–1.01)
Reference category: sedentary PA
 mild PA-0.16 (0.22)0.85 (0.55–1.30)
 moderate PA-0.32 (0.22)0.72 (0.47–1.10)
 high PA-0.52 (0.22)*0.59 (0.38–0.91)
Reference category: normal weight
 underweight-0.05 (0.40)0.95 (0.43–2.03)
 overweight0.29 (0.07)**1.34 (1.16–1.55)
 obese0.61 (0.08)**1.85 (1.58–2.16)
Reference category: male gender
 female gender0.44 (0.06)**1.55 (1.38–1.75)
Reference category: Low Income
Low to Middle-0.18 (0.11)0.84 (0.68–1.04)
Middle-0.46 (0.11)**0.63 (0.51–0.78)
Middle to High-0.38 (0.10)**0.68 (0.56–0.83)
High-0.51 (0.10)**0.60 (0.49–0.73)

R2 for final regression equation = .23 (Nagelkerke), Model x2(13) = 1079.50, p < .01;

N = 5802;

* p < .05;

** p < .01;

Beta weights are from the final regression equation;

R2 for final regression equation = .23 (Nagelkerke), Model x2(13) = 1079.50, p < .01; N = 5802; * p < .05; ** p < .01; Beta weights are from the final regression equation; Finally, we examined the influence of physical activity on developing musculoskeletal pain in the 10 years following baseline by examining only participants who reported being free at baseline (n = 3704). Pain status at follow up was used as the dependent variable and age, physical activity level, BMI, gender, and wealth quintile were entered in one step as predictors into the logistic regression equation. Out of 3704 participants, 1058 participants reported being frequently troubled by musculoskeletal pain ten years after baseline. It can be seen from the beta weights for the final regression equation (see Table 4) that engaging in high levels of physical activity was associated with a reduced risk of developing pain complaints after 10 years. Participants in the highest three wealth quintiles were also less likely to develop musculoskeletal pain compared to those in the lowest quintile. Being female, overweight, or obese increased the risk of suffering from musculoskeletal pain complaints after ten years.
Table 4

Logistic regression for the longitudinal relationship between physical activity and musculoskeletal pain among those reporting no pain at baseline.

β (SE)Odds Ratio (95% Confidence Interval)
Intercept-1.10 (0.50)
Age0.01 (0.01)1.00 (1.00–1.02)
Reference category: sedentary PA
 mild PA-0.56 (0.36)0.57 (0.28–1.17)
 moderate PA-0.64 (0.35)0.53 (0.26–1.06)
 high PA-0.81 (0.36)*0.45 (0.22–0.91)
Reference category: normal weight
 underweight-0.40 (0.56)0.67 (0.19–1.82)
 overweight0.33 (0.09)**1.39 (1.16–1.66)
 obese0.62 (0.10)**1.85 (1.52–2.26)
Reference category: male gender
 female gender0.43 (0.08)**1.54 (1.33–1.79)
Reference category: Low Income
Low to Middle-0.03 (0.14)0.98 (0.74–1.29)
Middle-0.30 (0.14)*0.74 (0.56–0.98)
Middle to High-0.31 (0.14)*0.74 (0.56–0.96)
High-0.40 (0.14)**0.67 (0.52–0.88)

N = 3740;

* p < .05;

** p < .01;

Beta weights are from the final regression equation;

R2 for final regression equation = .05 (Nagelkerke), Model x2(12) = 118.23, p < .01;

N = 3740; * p < .05; ** p < .01; Beta weights are from the final regression equation; R2 for final regression equation = .05 (Nagelkerke), Model x2(12) = 118.23, p < .01;

Discussion

This study found that physical activity has a beneficial influence on musculoskeletal pain complaints in a sample of older adults living in England, both cross-sectionally and longitudinally. This relationship existed over and above the influence of age, weight, gender, and wealth on pain. Being overweight or obese, female, having existing musculoskeletal pain, and having low wealth were found to predispose individuals to report frequent musculoskeletal pain complaints 10 years later. These factors were all significant independently of each other. The current study is the first to examine the concurrent contributions of these variables to the risk of experiencing musculoskeletal pain complaints cross-sectionally and longitudinally in a large sample of older adults. In our cross-sectional analysis, all levels of physical activity were found to be associated with a lower risk of reporting being troubled by musculoskeletal pain, over and above gender, weight, and wealth. Longitudinally, however, only high physical activity was associated with a lower probability of reporting being troubled by musculoskeletal pain ten years later. Physical activity has a beneficial effect on weight and may further improve bone mass and muscle function, prevent falls, as well as improve general health [31]. Further, physical activity may positively impact pain by elevating mood [32], reducing stress [33], and enhancing descending pain modulation [17]. Some investigations suggest a U-shaped relationship between physical activity and pain [21], whereby low and high levels of activity are related to increased pain, suggesting it can be both a risk and preventative factor. The current study did not find a U-shaped relationship between pain and physical activity; in the cross-sectional analysis all levels of physical activity were associated with a lower risk of pain than being sedentary, and in the longitudinal analysis high physical activity was associated with a lower risk of reporting musculoskeletal pain than being sedentary. However, the measure of physical activity used in this study precludes identification of those who engage in excessive levels of exercise and may therefore be at higher risk of injury and pain. Furthermore, participants’ relatively old age may be associated with reduced exercise intensity and frequency, further obscuring the proposed U-shaped relationship. Nevertheless, the current study suggests that engaging in high physical activity may be beneficial in preventing or alleviating musculoskeletal pain complaints. Current musculoskeletal pain complaints were the strongest predictor of future pain, suggesting that participants may suffer from pain for extended periods of time. Chronic pain is defined as pain lasting for more than three months [34], but the majority suffer for longer periods. A study among European chronic pain patients found that 59% of respondents had suffered from pain for between 2 and 15 years [22]. The reported association between existing and future musculoskeletal pain complaints is therefore not surprising and only serves to highlight the importance of adequately identifying, treating, and preventing pain. The current investigation corroborates findings that women are at higher risk of reporting being troubled from musculoskeletal pain [22, 23]. The exact mechanisms underlying gender differences in pain are unknown but have been hypothesised to be an interaction between biological, psychological, and sociocultural factors [35]. Differences in levels of sex hormones, such as oestrogen, progesterone, and testosterone, may contribute to the marked sex-related differences in pain [35-37]. Hormonal differences may also affect the processing of pain-related stimuli in the brain, with women showing lower activation in pain inhibitory brain regions [38]. Differences in psychosocial aspects, such as pain catastrophizing and self-efficacy, have also been suggested to mediate sex differences in pain responsivity. Women tend to engage in more catastrophic thinking around pain and have lower self-efficacy compared to men [35, 39], which is associated with greater pain. Finally, sociocultural beliefs pertaining to femininity and masculinity may influence pain reporting [35]. Reporting pain is societally more accepted among women than men, which may explain part of the observed differences. There is currently no consensus as to the exact nature of the relationship between pain and obesity [40]. The present study’s longitudinal nature lends credence to the notion that obesity is a precursor to musculoskeletal pain, but the reverse cannot be excluded based on these data, as obesity itself was not manipulated. There are two main hypotheses explaining the effect of obesity on pain [40]. First, it has been hypothesised that joint degradation due to excessive body mass may predispose individuals to develop osteoarthritis, especially in the lower back, knee, and hip joints. Second, obese individuals tend to have higher levels of certain inflammatory markers, such as tumour necrosis factor α, interleukin 6, and C-reactive protein, which may produce a hyperalgesic state [26]. Alternatively, pain may also predispose individuals to become obese because of reduced activity. A sedentary lifestyle, due to pain complaints, may lead to a calorie surplus, which may be negatively reinforced by the analgesic effect of food consumption [40]. Nevertheless, what the present study shows is that obesity is an important factor when it comes to musculoskeletal pain. Regardless of the directionality of the causal link, reducing obesity is likely to have a positive effect not only on musculoskeletal pain but on a range of other health-related aspects, such as the cardiovascular system. Furthermore, it is reasonable to assume that reductions in pain may serve to increase individuals’ inclination to exercise, further reducing obesity likely having overall positive effects on health. Wealth was associated with a lower risk of musculoskeletal pain complaints. The negative effects on mood and general health stemming from economic stress are well documented [41]. Depression and pain have overlapping neuroanatomical pathways and share neurobiological substrates, which may explain why depressive symptomologies are associated with pain [42, 43] and ultimately why low wealth is associated with musculoskeletal pain complaints [25]. Furthermore, a high disposable income may also enable individuals to seek extra care, aside from that covered by insurances or national health services, to treat ailments. On the other hand, pain is a major contributor to work absenteeism, reduced employability, and loss of employment. All of which are associated with a loss of income and therefore negatively affect individuals’ wealth. Given the nature of the data, the directionality of this effect cannot be elucidated. The current study’s strengths include a large representative sample of older adults residing in England, a follow-up period of 10 years, as well as a range of self-reported and objective predictor variables. The outcome variable was a self-report of whether participants were frequently troubled by pain. As such, responses may have been influenced by recall bias and social desirability. Furthermore, use of a dichotomous variable does not allow inferences to be drawn as to the predictors of pain intensity. Nevertheless, the same outcome variable has been used in previous investigations, such as Smith et al. [28]. This research was concerned specifically with the association between physical activity and pain in older adults (aged 50+) and it should therefore be noted that the conclusions may not apply to younger adults. Furthermore, self-reported physical activity levels may be subject to recall bias, which may lead to misclassification. In conclusion, the aim of this study was to examine the relationship between physical activity and musculoskeletal pain complaints in a sample of older adults. It showed that high physical activity is associated with a reduced likelihood of developing musculoskeletal pain complaints compared to sedentariness, over and above age, weight, gender, and wealth. These findings provide insights that may inform interventions aimed at reducing the risk of developing frequent musculoskeletal pain complaints. In particular, weight control, increasing physical activity and managing wealth inequality should be considered when developing preventative strategies to reduce pain. 30 Dec 2021
PONE-D-21-34233
Physical activity protects against pain in older adults
PLOS ONE Dear Dr. Niederstrasser, Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.
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For instructions see: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols. We look forward to receiving your revised manuscript. Kind regards, David Meyre Academic Editor PLOS ONE Journal Requirements: When submitting your revision, we need you to address these additional requirements. 1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf [Note: HTML markup is below. Please do not edit.] Reviewers' comments: Reviewer's Responses to Questions Comments to the Author 1. Is the manuscript technically sound, and do the data support the conclusions? The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. Reviewer #1: Yes Reviewer #2: Yes ********** 2. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: Yes Reviewer #2: Yes ********** 3. Have the authors made all data underlying the findings in their manuscript fully available? The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified. Reviewer #1: Yes Reviewer #2: Yes ********** 4. Is the manuscript presented in an intelligible fashion and written in standard English? PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here. Reviewer #1: Yes Reviewer #2: Yes ********** 5. Review Comments to the Author Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters) Reviewer #1: I would like to extend my congratulations to the authors. DEal with huge datasets is not a simple task and you should be proud of your work. The paper is well written and present relevant data; however, the conclusions seem to be a little overestimated. For instance, on page 9 the authors state that, on a cross-sectional point of view, being physically active decreases the risk of experiencing musculoskeletal pain and on page 10, on a longitudinal point analysis, being physically active decreases the risk of experiencing musculoskeletal pain, however, the OR presented on table 3 regarding the longitudinal analysis only support this conclusion for those engaging in vigorous physical activity. The same goes for the discussion section, where authors lump all the results together as if all the analysis were statistically significant. These should be addressed more carefully to fully describe the finding, eliminating the chance of misleading the reader. Also, I suggest that in the discussion section the authors should comment about their subjects’ demographics, specifically regarding the advanced age and above-average wealth status of the subjects. These could be major confounding factors and should be acknowledge on the paper. Reviewer #2: The study addressed a very important question about physical activity and musculoskeletal pain using a large dataset. However, the aims of the paper may not be consistent with the title. It seems like the paper is looking at multiple factors instead of PA only. 1. Abstract: the information about how pain and PA were assessed were lacking. What is the definition of "no physical activity"? 2. Intro: 1st paragraph, which country were you referring to when you mentioned the prevalence of pain? Is this the prevalence for community-dwelling older people or other settings? 3. Intro: the last sentence in the 1st paragraph may not smoothly transit to the second paragraph. It sounds like you are looking at factors contributing to persistent pain complaints and then the next paragraph is about the protective effects of PA on pain. 4. The second paragraph on page 4, you used the term "interact", it sounds like you are examining the interaction between PA and other factors which is not in your analyses. Again, is the evidence you provided specifically for older adults? This needs to be clear. 5. After I read the intro, I think this paper is focusing on PA and pain because you have mentioned a lot about this association, but in the results and discussions, it seems like you are looking at multiple factors contributing to pain. 6. Methods: the sample section is not clear. You said between waves 1 and 4 were eligible, but before and after that sentence, you only mentioned waves 2 and 4. 7. In terms of the pain and PA assessment, what is the time frame? Is this self-reported pain in the past year or past month? The same question for PA assessment. Older adults may not be able to accurately recall pain or PA if it is a long time frame. 8. Results: page 9, the word "increase" implies longitudinal association. Better to say "higher level of PA was associated with lower likelihood of reporting being troubled...." 9. Table 2, given the small beta coefficient for age, better to scale it to 5 or 10 years. 10. Results: page 10, "our analysis corrected for musculoskeletal pain complaints existing at baseline". The word "corrected" may not be accurate, better to say "adjusted for baseline pain". The sentence "the more PA an individual engaged in at baseline the less likely they were..." is not reflecting the results in table 3. The only significant finding is vigorous PA versus sedentary PA. The interpretation of the results should be accurate. 11. Discussion: second paragraph, the first sentence is too ambitious. This study is observational and not an intervention. The associations did not translate to "protect effects". In addition, better to add discussion about potential pathways from PA to pain in this paragraph. The last sentence "the current study suggests that all levels of physical activity are beneficial..." is not reflecting the results. Based on Table 3, it is not all levels of PA, only vigorous PA is associated with lower likelihood of pain. 12. Limitation: may add limitation of self-reported PA which leads to recall bias and misclassification. 13. Overall, the author mentioned the outcome is "development of persistent pain" which implies changes in pain status. I don't think the analysis simply adjusting for baseline pain is answering this question. Better to categorize participants into groups: no pain in both visits, incident pain (no pain at baseline), recovered pain, and persistent pain (pain in both visits). ********** 6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files. If you choose “no”, your identity will remain anonymous but your review may still be made public. Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy. Reviewer #1: Yes: DANIEL POZZOBON Reviewer #2: No [NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.] While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step. 11 Jan 2022 Reviewer #1: I would like to extend my congratulations to the authors. Deal with huge datasets is not a simple task and you should be proud of your work. Thank you very much for the kind words. We appreciate the support. The paper is well written and present relevant data; however, the conclusions seem to be a little overestimated. For instance, on page 9 the authors state that, on a cross-sectional point of view, being physically active decreases the risk of experiencing musculoskeletal pain and on page 10, on a longitudinal point analysis, being physically active decreases the risk of experiencing musculoskeletal pain, however, the OR presented on table 3 regarding the longitudinal analysis only support this conclusion for those engaging in vigorous physical activity. The same goes for the discussion section, where authors lump all the results together as if all the analysis were statistically significant. These should be addressed more carefully to fully describe the finding, eliminating the chance of misleading the reader. Thank you for pointing out these oversights. We have adjusted the text following your suggestions (“Beta weights for the final regression equation (see Table 3) indicated that engaging in mild, moderate, and high physical activity was protective against developing musculoskeletal pain complaints.”, pg. 12). We have amended the discussion section in various places following the reviewer’s suggestions (“Longitudinally, however, only high physical activity was associated with a lower probability of reporting being troubled by musculoskeletal pain ten years later.” pg. 14; “Nevertheless, the current study suggests that engaging in high physical activity may be beneficial in preventing or alleviating musculoskeletal pain complaints.”, pg. 15). Also, I suggest that in the discussion section the authors should comment about their subjects’ demographics, specifically regarding the advanced age and above-average wealth status of the subjects. These could be major confounding factors and should be acknowledge on the paper. We have added a section explaining the possible confounding influence of participants’ advanced age and the self-report assessment (“This research was concerned specifically with the association between physical activity and pain in older adults (aged 50+) and it should therefore be noted that the conclusions may not apply to younger adults. Furthermore, self-reported physical activity levels may be subject to recall bias, which may lead to misclassification.”, pg. 17). While wealth is known to be associated with both physical activity and pain, as our paper also demonstrates, it is not necessarily the case that the participants selected in this study have a higher wealth status than average. The ELSA data set is specifically designed to be representative of older adults living in England and wealth distribution within the data set should therefore also be representative of wealth distribution in England among this demographic. Reviewer #2: The study addressed a very important question about physical activity and musculoskeletal pain using a large dataset. However, the aims of the paper may not be consistent with the title. It seems like the paper is looking at multiple factors instead of PA only. We thank reviewer 2 for their comments and suggested revisions. We have taken these on board and revised the manuscript to improve clarity. We feel the paper has been greatly improved following revisions based on suggestions by reviewer 2. 1. Abstract: the information about how pain and PA were assessed were lacking. What is the definition of "no physical activity"? Thank you for pointing out these oversights in the abstract. We have added information regarding how pain and physical activity were assessed (“Participants self-reported their physical activity level and whether they were often troubled by bone, joint, or muscle pain”, pg. 2). There was in fact no category denoting total absence of physical activity. The category reflecting the lowest level of physical activity was “sedentary”. The abstract has been changed to reflect this correction. The definition of “sedentariness” in the current context was as follows: Not working or sedentary occupation, engages in mild exercise 1–3 times a month or less, with no moderate or vigorous activity. We have added definitions of physical activity levels to the method section (pgs. 6-7). We have also changed the highest level of physical activity level from “vigorous” to “high” to more closely reflect the nomenclature used in the ELSA documentation. 2. Intro: 1st paragraph, which country were you referring to when you mentioned the prevalence of pain? Is this the prevalence for community-dwelling older people or other settings? The figure refers to patient populations in US nursing homes and females in developing countries. We realise it may be more appropriate to report values from a UK-based population which are more comparable to the current study’s population. The section has been amended accordingly (“The prevalence of pain increases with age, with up to 62% of the over 75 age group in the UK reporting persistent pain complaints 2”, pg. 3). 3. Intro: the last sentence in the 1st paragraph may not smoothly transit to the second paragraph. It sounds like you are looking at factors contributing to persistent pain complaints and then the next paragraph is about the protective effects of PA on pain. We have amended the starting sentence of the second paragraph to begin with the negative effects of sedentariness (“Studies have suggested that sedentary behaviour may lead to disuse symptoms and result in greater pain sensitivity 3, while being physically active may have protective effects against the occurrence of pain complaints and its consequences 1.”, pg. 3). 4. The second paragraph on page 4, you used the term "interact", it sounds like you are examining the interaction between PA and other factors which is not in your analyses. Again, is the evidence you provided specifically for older adults? This needs to be clear. We have removed the word “interact” and changed the sentence’s wording (“Furthermore, there may be additional factors associated with greater propensity to report pain complaints in older age”, pg. 4). We have further clarified that the presented evidence is for the general population and not older adults specifically. 5. After I read the intro, I think this paper is focusing on PA and pain because you have mentioned a lot about this association, but in the results and discussions, it seems like you are looking at multiple factors contributing to pain. The reviewer is correct in stating that the paper’s main focus is on the association between physical activity and pain. We feel, however, that it is important to appreciate alternative influences and factors when examining this association. We therefore decided to include additional factors in our analysis to show that physical activity predicts pain over and above the influences of these other variables. We have clarified at the beginning and end of the discussion: “This study found that physical activity has a beneficial influence on musculoskeletal pain complaints in a sample of older adults living in England, both cross-sectionally and longitudinally. This relationship existed over and above the influence of age, weight, gender and wealth on pain.” (p. 14) and “In conclusion, the aim of this study was to examine the relationship between physical activity and musculoskeletal pain complaints in a sample of older adults. It showed that high physical activity is associated with a reduced likelihood of developing musculoskeletal pain complaints compared to sedentariness, over and above age, weight, gender and wealth.” (p. 18). 6. Methods: the sample section is not clear. You said between waves 1 and 4 were eligible, but before and after that sentence, you only mentioned waves 2 and 4. We realise the sample section is not written with sufficient clarity and have amended the section to rectify this. In short, waves 1 and 3 could not function as baseline assessments as they lacked essential variables (recorded variables vary between waves in the ELSA data set). Participants were eligible for inclusion if their data were present in either waves 2 and 7 or 4 and 9, since the longitudinal assessment spanned 10 years. 7. In terms of the pain and PA assessment, what is the time frame? Is this self-reported pain in the past year or past month? The same question for PA assessment. Older adults may not be able to accurately recall pain or PA if it is a long time frame. There is no timeframe specified in the question assessing physical activity, according to the official ELSA documentation. The questions on physical activity status were extracted from a validated physical activity interview and have been used previously in the HSE physical activity assessment and other work using the data longitudinally 7. Similarly, there is no specific timeframe attached to the question regarding pain. 8. Results: page 9, the word "increase" implies longitudinal association. Better to say "higher level of PA was associated with lower likelihood of reporting being troubled...." Thank you for this suggestion. We have adjusted the paragraph to reflect this change. 9. Table 2, given the small beta coefficient for age, better to scale it to 5 or 10 years. Our understanding of this point is that the reviewer would like us to change the continuous variable of age into an ordinal variable, whereby participants are put into age groups such as 50-59, 60-69, etc. Our preference is to keep the variable continuous because this maximises its variance and thus information value. We do not see the small beta coefficient as surprising or problematic because the sample is specifically of older adults. If the sample had a wider age range, then we would expect to see a relationship between age and presence/absence of pain. 10. Results: page 10, "our analysis corrected for musculoskeletal pain complaints existing at baseline". The word "corrected" may not be accurate, better to say "adjusted for baseline pain". The sentence "the more PA an individual engaged in at baseline the less likely they were..." is not reflecting the results in table 3. The only significant finding is vigorous PA versus sedentary PA. The interpretation of the results should be accurate. We have replaced “corrected” with “adjusted”, as requested. Thank you for pointing out the oversight regarding the effects of vigorous physical activity. This has been corrected (“Beta weights for the final regression equation (see Table 3) indicated that engaging in high physical activity was associated with lower probability of reporting being troubled by musculoskeletal pain ten years later.”, pg. 12). 11. Discussion: second paragraph, the first sentence is too ambitious. This study is observational and not an intervention. The associations did not translate to "protect effects". In addition, better to add discussion about potential pathways from PA to pain in this paragraph. The last sentence “the current study suggests that all levels of physical activity are beneficial…” is not reflecting the results. Based on Table 3, it is not all levels of PA, only vigorous PA is associated with lower likelihood of pain. We have amended the first sentence in the second paragraph of the discussion to reflect the findings more accurately (“In our cross-sectional analysis, all levels of physical activity were found to be associated with a lower risk of reporting being troubled by musculoskeletal pain, over and above gender, weight, and wealth. Longitudinally, however, only high physical activity was associated with a lower probability of reporting being troubled by musculoskeletal pain ten years later.” pg. 14). We have added a brief discussion of potential pathways from physical activity to pain to the paragraph (“Further, physical activity may positively impact pain by elevating mood 6, reducing stress 4, and enhancing descending pain modulation 5.”, pgs. 14-15). We have corrected the statement regarding all levels of physical activity being associated with lower likelihood of reporting pain complaints longitudinally. We have also adjusted the manuscript’s title to reflect the changes. 12. Limitation: may add limitation of self-reported PA which leads to recall bias and misclassification. The requested additions have been made (“Furthermore, self-reported physical activity levels may be subject to recall bias, which may lead to misclassification.” pg. 17). 13. Overall, the author mentioned the outcome is "development of persistent pain" which implies changes in pain status. I don't think the analysis simply adjusting for baseline pain is answering this question. Better to categorize participants into groups: no pain in both visits, incident pain (no pain at baseline), recovered pain, and persistent pain (pain in both visits). We understand the reviewer’s concerns about whether our analysis explores the development of persistent pain or not. We have therefore added an additional analysis to the paper where we predict pain at Time 2 in the subset of participants who did not report pain at Time 1. We feel that this looks at the issue of the development of pain more specifically. However, we have retained our original analysis where we adjusted for baseline pain as we feel that together these analyses build a broader (and consistent) picture of the relationships. We feel that this addresses the research question more directly than using the four groups the reviewer suggests as a dependent variable. We appreciate the reviewer suggesting an alternative analysis. We are, however, not aware of an analysis more appropriate than the current to demonstrates the effect we describe in the manuscript. We would appreciate if the reviewer could elaborate on the requested analysis. References: 1. Bergman S: Public health perspective - how to improve the musculoskeletal health of the population. Best Pract Res Clin Rheumatol [Internet] 21:191–204, 2007 [cited 2021 Jun 30]. Available from: https://www.sciencedirect.com/science/article/pii/S1521694206001161?casa_token=50MwAUpTJnkAAAAA:f2qXyUAkuRUYbYzRWW6X6uNa95P30cmva_5uI95qsJEbj0w77ryl7i9pcc8RP2qhNwM0iwzF 2. Fayaz A, Croft P, Langford RM, Donaldson LJ, Jones GT: Prevalence of chronic pain in the UK: A systematic review and meta-analysis of population studies. BMJ Open [Internet] 6:, 2016 [cited 2022 Jan 7]. Available from: https://bmjopen.bmj.com/content/6/6/e010364?cpetoc 3. Law LF, Sluka KA: How does physical activity modulate pain? Pain. 2017. 4. Mücke M, Ludyga S, Colledge F, Gerber M: Influence of Regular Physical Activity and Fitness on Stress Reactivity as Measured with the Trier Social Stress Test Protocol: A Systematic Review. Sport Med Springer International Publishing; 48:2607–22, 2018. 5. Naugle KM, Riley JL: Self-reported physical activity predicts pain inhibitory and facilitatory function. Med Sci Sports Exerc [Internet] NIH Public Access; 46:622–9, 2014 [cited 2021 Jul 20]. Available from: /pmc/articles/PMC3906218/ 6. Penedo FJ, Dahn JR: Exercise and well-being: A review of mental and physical health benefits associated with physical activity. Curr Opin Psychiatry [Internet] Curr Opin Psychiatry; 18:189–93, 2005 [cited 2022 Jan 6]. Available from: https://pubmed.ncbi.nlm.nih.gov/16639173/ 7. Rogers NT, Marshall A, Roberts CH, Demakakos P, Steptoe A, Scholes S: Physical activity and trajectories of frailty among older adults: Evidence from the English Longitudinal Study of Ageing. Ginsberg SD, editor. PLoS One [Internet] 12:e0170878, 2017 [cited 2018 May 30]. Available from: http://dx.plos.org/10.1371/journal.pone.0170878 Submitted filename: Response to Reviewers.docx Click here for additional data file. 18 Jan 2022 Associations between Pain and Physical Activity among older Adults PONE-D-21-34233R1 Dear Dr. Niederstrasser, We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements. Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication. An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org. If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org. Kind regards, David Meyre Academic Editor PLOS ONE Additional Editor Comments (optional): Reviewers' comments: 21 Jan 2022 PONE-D-21-34233R1 Associations between Pain and Physical Activity among older Adults Dear Dr. Niederstrasser: I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department. If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org. If we can help with anything else, please email us at plosone@plos.org. Thank you for submitting your work to PLOS ONE and supporting open access. Kind regards, PLOS ONE Editorial Office Staff on behalf of Dr. David Meyre Academic Editor PLOS ONE
  40 in total

Review 1.  Physical activity and low back pain: a systematic review of recent literature.

Authors:  Hans Heneweer; Filip Staes; Geert Aufdemkampe; Machiel van Rijn; Luc Vanhees
Journal:  Eur Spine J       Date:  2011-01-09       Impact factor: 3.134

2.  Obesity and pain.

Authors:  Donald Scott McVinnie
Journal:  Br J Pain       Date:  2013-11

3.  Associations between recreational exercise and chronic pain in the general population: evidence from the HUNT 3 study.

Authors:  Tormod Landmark; Pål Romundstad; Petter C Borchgrevink; Stein Kaasa; Ola Dale
Journal:  Pain       Date:  2011-05-23       Impact factor: 6.961

4.  Low-intensity physical activity is associated with reduced risk of incident type 2 diabetes in older adults: evidence from the English Longitudinal Study of Ageing.

Authors:  P Demakakos; M Hamer; E Stamatakis; A Steptoe
Journal:  Diabetologia       Date:  2010-05-22       Impact factor: 10.122

5.  Pain perception threshold in major depression.

Authors:  G Adler; W F Gattaz
Journal:  Biol Psychiatry       Date:  1993-11-15       Impact factor: 13.382

6.  Role of health care professionals in multidisciplinary pain treatment facilities in Canada.

Authors:  Philip Peng; Jennifer N Stinson; Manon Choiniere; Dominique Dion; Howard Intrater; Sandra LeFort; Mary Lynch; May Ong; Saifee Rashiq; Gregg Tkachuk; Yves Veillette
Journal:  Pain Res Manag       Date:  2008 Nov-Dec       Impact factor: 3.037

7.  Self-reported physical activity predicts pain inhibitory and facilitatory function.

Authors:  Kelly M Naugle; Joseph L Riley
Journal:  Med Sci Sports Exerc       Date:  2014-03       Impact factor: 5.411

8.  Common chronic pain conditions in developed and developing countries: gender and age differences and comorbidity with depression-anxiety disorders.

Authors:  Adley Tsang; Michael Von Korff; Sing Lee; Jordi Alonso; Elie Karam; Matthias C Angermeyer; Guilherme Luiz Guimaraes Borges; Evelyn J Bromet; K Demytteneare; Giovanni de Girolamo; Ron de Graaf; Oye Gureje; Jean-Pierre Lepine; Josep Maria Haro; Daphna Levinson; Mark A Oakley Browne; Jose Posada-Villa; Soraya Seedat; Makoto Watanabe
Journal:  J Pain       Date:  2008-07-07       Impact factor: 5.820

9.  Age as a factor in admission to chronic pain rehabilitation.

Authors:  W G Kee; S J Middaugh; S Redpath; R Hargadon
Journal:  Clin J Pain       Date:  1998-06       Impact factor: 3.442

Review 10.  The correlation between stress and economic crisis: a systematic review.

Authors:  Nicola Mucci; Gabriele Giorgi; Mattia Roncaioli; Javier Fiz Perez; Giulio Arcangeli
Journal:  Neuropsychiatr Dis Treat       Date:  2016-04-21       Impact factor: 2.570

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